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This is a tutorial on how to reproduce a project created with the
worcs
package. At the core of a typical worcs
projects is an ‘R Markdown’ document, containing prose and analysis
code. This document can be compiled, or “knitted”, to reproduce the
analyses. This tutorial will guide you through the steps necessary to
make that happen.
You can skip these steps if you have a recent and working installation of ‘RStudio’ and ‘R’.
install.packages("package name")
install.packages("worcs", dependencies = TRUE)
tinytex::install_tinytex()
renv::consent(provided = TRUE)
WORCS projects are typically hosted on ‘GitHub’, or another ‘Git’ remote repository.
The recommended way to obtain a local copy of the project repository is to “clone” it.
On ‘GitHub’, this is done by clicking the green button labeled “Code”. Clicking it reveals the HTTPS link to the project repository (see below). Copy this link to the clipboard by clicking the clipboard icon next to it.
Next, open an RStudio instance and run the following code in the
console, replacing https://github.com/username/reponame.git
with the HTTPS address you just copied to clipboard, and replacing the
c:/where/you/want/the/repo
with the location on your hard
drive where you want to clone the repository:
gert::git_clone("https://github.com/username/reponame.git", path = "c:/where/you/want/the/repo")
Note: While it is also possible to download a compressed (ZIP) archive containing the project (see the image above), this has an important limitation: a repository downloaded via the GitHub interface is, itself, not a Git repository! This is a peculiarity of the GitHub interface. This might result in unexpected behavior when using any WORCS functionality that relies on Git for version control. Thus, as a general rule, we advise cloning projects instead.
Most projects can be opened by loading the ‘.RProj’ file in the main folder. This should be explained in the project ‘README.md’ as well.
You will need to restore the packages used by the authors, using the
renv
package. See this
article for more information about renv
.
With the project open in ‘RStudio’, type the following in the console:
renv::restore()
The entry point is the core document that can be executed to reproduce the analysis. This is typically a manuscript, or occasionally an R-script file. Use the following function to open the entry point file in ‘RStudio’:
load_entrypoint()
From worcs
version 0.1.12, projects can be reproduced
using the function reproduce()
. This function will evaluate
the reproducibility recipe stored in the .worcs
project
file, and checks whether the resulting endpoints have the correct
checksums (i.e., are unchanged relative to the authors’ original
work).
Sometimes, authors have not made the original data available. In this case, the project ought to contain a synthetic data file with similar properties to the original data. This synthetic data allows you to verify that the analyses can be run, and that the code is correct. The results will, however, deviate from the original findings and should not be substantively interpreted.
Authors may use the function notify_synthetic()
to
generate a message in the paper when a synthetic dataset is used.
Authors should also provide information in the README.md file on how to
obtain access to the original data in case an audit is warranted. Please
read the WORCS paper [@vanlissaWORCSWorkflowOpen2021] for more
information about how checksums are used so that auditors can verify the
authenticity of the original data.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.